In the tension between large-scale analysis and accuracy - Identifying and analysing intra-urban (sub-)centre structures comparing official 3D-building models and TanDEM-X nDSMs

Abstract

Intra-urban polycentricity has often been described by a balanced distribution of jobs/residences outside the traditional core cities in so-called (sub-)centres. Recently, this purely socioeconomic view has changed, so that centres are also increasingly understood as a physical manifestation of spatial development policies. Built-up volumes derived from 3D-building models are therefore frequently used instead of or as complement to employment/population figures when studying intra-urban polycentricity. However, such data are expensive and not available universally and permit only geographically limited investigations to date. To overcome this constraint, we investigate whether globally available and consistent TanDEM-X nDSMs (TDX) provide a valid data base for intra-urban polycentricity research based on built-up volumes. Our study focuses on four urban regions in Germany for which we have obtained official 3D-building models (LoD-1). For each study site, we derive aggregated built-up volumes from the TDX and the LoD-1 data and identify (sub-)centres. We use three centre identification algorithms to account for the diversity of methods and outcomes. We consider the LoD-1 (sub-)centres as reference and the TDX (sub-)centres as the entities to be reviewed. First, we quantify their spatial agreement and compare if polycentricity measures calculated based on both data sets lead to similar results. Second, we explore possible causes for discrepancies between the TDX/LoD-1 (sub-)centres. We find high spatial resemblances between TDX and LoD-1 (sub-)centres. Accordingly, we observe that polycentricity measures display similar trends among the two data sets. Nevertheless, we also show that the agreement between TDX and LoD-1 centres can be affected in uneven terrain, in sparsely built-up areas, and by the algorithms used to identify (sub-)centres. Overall, our results suggest that TDX nDSMs reflect the distribution of built-up structures in sufficient detail so that local-spatial densifications – here equated with (sub-)centres – can be appropriately studied. We therefore conclude that TDX data offer a great potential for the thematic domain of morphological urban analysis at large scale.